New hope for treating cancer? Patterns seen in 12 types of tumors

Los Angeles Times

09-27-13

Sept. 26--Examining the molecular profiles of tumors from 12 different types of
cancers, scientists working with the National Institutes of Health-backed Cancer
Genome Atlas said Thursday they had found striking similarities between tumors
originating in different organs.

Their discoveries, made possible by improvements in sequencing technologies and
computing methods, could herald a day when cancers are treated based on their
genetic profiles, rather than on their tissue of origin, said UC Santa Cruz
biomolecular engineer Josh Stuart, a participant in the project and coauthor of
a commentary discussing its findings released Thursday by the journal Nature
Genetics.

Eventually, such a shift in thinking could lead researchers to new treatments
for hard-to-treat cancers, Stuart said, in an interview with the Los Angeles
Times.

If scientists can find molecular similarities, say, between a rare form of
breast cancer and a form of ovarian cancer, they might be able to use a drug
known to target the ovarian tumor to treat the unusual subtype of breast cancer.

"Hopefully fewer patients will be left out on their own," Stuart said.

The Cancer Genome Atlas or TCGA, which has been underway since 2006, seeks to
catalog the DNA and other molecular features of thousands of different tumors
from a variety of cancer types. (The Los Angeles Times reported on findings from
two earlier Cancer Genome Atlas studies in May.) By identifying how genes are
scrambled up in tumors and what effects those changes have in cells, the
thinking goes, researchers might be able to understand better how different
cancers progress, and find the best treatments for particular tumor types and
subtypes.

The Pan-Cancer initiative that Stuart is involved with carries the analysis
further, comparing cancers of different types to see what patterns emerge. The
team looked at TCGA data -- gene mutations, changes in the numbers of copies of
genes, and measures of how the genes were behaving -- from tumors sampled from
thousands of patients who had 12 different cancers (including tumor types in the
brain, head and neck, kidney, lung, breast, ovary, cervix, colon and rectum and
one type of leukemia.)

The cross-cancer comparison was a project many researchers had wanted to pursue,
Stuart said. Some had already noticed similarities as they studied various
tumors as part of TCGA. "We'd say, hey, I recognize that copy number profile in
that breast cancer. Didn't we see it in ovarian cancer last month?" he said.

Comparing different types of tumors is useful because it lets scientists learn
more about how cancers behave than looking at one type on its own can. Cancers
are a jumble of cells. Looking at just one type of tumor might let a researcher
identify the jumble within that certain cancer, but doesn't necessarily point to
the mechanism that triggered the cancer in the first place, Stuart said.

But looking at several cancers at once and finding commonalities can help tease
out the cell of origin, he added.

Over the coming months, the collaboration will publish dozens of papers
detailing what researchers found in the cancers. Two such papers were published
Thursday, also in Nature Genetics. One noted similarities in gene copy-number
changes across cancers. The other classified tumors and tumor subtypes according
to their molecular profiles, identifying two large classes that had not been
identified previously (one set of cancers where genetic mutations predominate,
and another where copy number changes predominate.) Nature Genetics also
published a second commentary about the Pan-Cancer initiative, delving into the
computing strategies scientists have devised to crunch vast stores of
tumor-related genetic data.

Stuart said that while the notion tumors of different origins might share
genetic signatures wasn't a new one, the TCGA Pan-Cancer effort finally lets
scientists dig in and see whether it's true.

"We just haven't had the data to step back and look at it all together and
connect the dots," he said. Over coming months, researchers will add tumors and
tumor types to the dataset, and will also analyze whole genome data.

"There's a lot to put in place," he said, noting therapies would be tested in
cells and lab animals before there were trials in people.

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